Deep slate report — 20261010

Generated 2026-10-11T05:19:20.926828-04:00 · schema deep_slate_diagnosis_v3 · fuses prediction review + forensic deep audit + official starter lines, with a Luna post-mortem.

Process, end to end

1. Settle review
complete
1 games vs official finals
2. Forensic deep audit
complete
per-game probability + pitcher impact
3. Deep diagnosis
built
0 losses attributed to a root cause
4. Luna post-mortem
received
9/8 sections; 1/1 games; 4/4 causes; 7/7 sources
5. Adjustment
skipped_open_rollback_monitor
6. Gating
shadow, manual + gated
production champion unchanged

Slate summary

Games
1
Hits
1
Misses
0
Winner accuracy
100%
Mean Brier (losses)
n/a
Mean total-run bias (losses)
n/a

Source coverage receipt

Which reports actually fed the diagnosis. A source shown as missing was not silently assumed.

SourceStatusEvidence suppliedPathBytes
prediction reviewloadedofficial outcomes and scoring errors/app/output/reports/prediction_review_20261010.json11425
forensic deep auditloadedprobability, provenance, starter and decision contracts/app/output/reports/PREDICTION_SYSTEM_DEEP_AUDIT_20261010.json30956
continuous learningloadedpipeline-stage quality, calibration, probability lineage, score distribution, and official starter comparisons/app/output/learning/continuous_learning_daily_20261010.json185336
detailed reportloadedfull game and simulation rendering/app/output/reports/detailed_20261010.html33426
ultra detailed player auditloadedplayer-level prediction trace/app/output/reports/20261010_ultra_detailed_player_audit.html1811791
structural auditloadedall invariant findings/app/output/reports/audit_report_20261010.html128231
integrity revision auditloadedstructural audit of every post-start revision of the slate's games/app/output/reports/audit_report_20261010_integrity_revision.html365249

High-level causal issue register

Deterministic findings across data integrity, model validation, calibration, score distribution, pipeline stages, simulation, and coverage. Critical is reserved for broken evidence or an unexplained contract violation; high marks material model/process risk. Each row pairs the action to take (Do this) with the wrong conclusion to avoid (Don't conclude).

SeverityDomainFinding and evidenceAffectedAction & guardrail
HIGHcalibrationPublished confidence buckets were poorly aligned on this slate
weighted absolute calibration error 0.4732 across 1 games
CHW@CLE
Do thisWatch the same confidence buckets over the full rolling window before changing any calibration weight.
Don't concludeA single slate has far too few games to establish a stable calibration curve.
HIGHmodel_validationValidated run models explain very little holdout variance
home/away/total R² = 0.0021/0.0309/0.0024
CHW@CLE
Do thisTreat exact run scores as low-confidence estimates, and look for stronger features or a better target before tuning the score tails.
Don't concludeA small positive R² only means the model beats guessing the average; it does not make the exact scores reliable.
INFOcoverageEvery settled game received structural QA
1/1 games structurally audited
CHW@CLE
Do thisKeep the per-game audit receipt in every report.
Don't concludeFull audit coverage does not cancel the findings raised inside the audited games.
INFOsimulationSimulation produced no winner-direction intervention on this slate
flip candidates 0; published flips 0
CHW@CLE
Do thisMeasure the simulation's contribution across rolling slates, separating score realization from winner flipping.
Don't concludeZero winner flips is not a defect and does not mean the simulation did no score-reconciliation work.

Cross-slate trends (persistent-pattern memory)

Window: 20260930, 20261001, , 20261003, 20261004, 20261005, 20261006, 20261007, 20261008, , 20261010 (10 prior slates loaded). Highest-confidence pick loss streak: 0 slate(s). Actionable pattern detected.

Escalated persistent patterns

A finding that has repeated at or beyond the escalation streak is no longer single-slate noise. It carries its target registered lever and an action-oriented guardrail.

FindingPersistenceTarget lever(s)DirectionGuardrail
simulation_inert_on_slate11 consecutive · 11 in windowsimulation.allow_scoreconfirm the simulation module is running, not silently no-opingsimulation_inert_on_slate has persisted 11 consecutive slates; this is no longer single-slate noise. Treat it as an actionable pattern and raise the code/diagnostic action named; do not force a parameter move.

Finding streaks across the window

FindingConsecutive slatesIncidencePresent nowFix type
pipeline_winner_instability02/11nocode/diagnostic
score_margin_compression03/11noparam
simulation_inert_on_slate1111/11yescode/diagnostic
single_slate_calibration_instability19/11yesparam
weak_run_model_signal19/11yescode/diagnostic

Metric direction across the window

MetricDirectionSeries (old → new)
winner_accuracyimproving0.75, 1.0, –, 1.0, 0.5, 0.0, 1.0, 0.75, 1.0, –, 1.0
weighted_calibration_errorregressing0.2317, 0.4832, –, 0.4705, 0.4806, 0.5291, 0.4642, 0.2272, 0.495, –, 0.4732
margin_biasimproving-2.75, -3.0, –, -0.25, 0.0, -0.5, -0.5, -1.75, -3.0, –, -1.0
team_run_error_on_lossesimproving2.0, –, –, –, 2.0, 3.5, –, 2.0, –, –, –

Pipeline stage regression

Every stored stage is scored against the same official finals. A later recovery remains visible; it does not erase an unstable intermediate flip.

StageWinner hitsAccuracyTeam-run MAETotal-run MAEMargin MAE
historical_ml1/1100%3.4716.9421.222
variance_applied1/1100%3.571
enhanced_prediction1/1100%4.591
kpi_layer1/1100%4.591
embedded_savant_run_environment1/1100%4.591
fundamental_edge_target_review1/1100%4.591
capped_target1/1100%4.591
simulation_result1/1100%4.591
published_final1/1100%4.591
TransitionΔ accuracyΔ hitsΔ team-run MAEΔ margin MAEGames whose winner/tie changed
historical_ml → variance_applied000.0289-0.2224
variance_applied → enhanced_prediction0010
enhanced_prediction → kpi_layer0000
kpi_layer → embedded_savant_run_environment0000
embedded_savant_run_environment → fundamental_edge_target_review0000
fundamental_edge_target_review → capped_target0000
capped_target → simulation_result0000
simulation_result → published_final0000

Probability lineage and calibration

All columns are pick-side probabilities, so away favorites are not accidentally compared using home-side semantics.

GameOutcomeRaw modelCalibratedGovernorScore coherencePublishedExplanation
CHW@CLEhit0.56270.53720.53720.53720.5268score coherence followed by matchup-recency guardrail
Pitcher versus batter: patterns across the whole slate

One blown start is noise. The same failure repeating across the slate is a model problem. These are the repeats.

Sides analyzedBroke on pitchingBroke on offenseBothVarianceMean starter ERA errorMean lineup runs vs proj
20101-1.93-2
Trained winner blend: does it reach the published number?

The blend mixes the trained win classifier with the margin-derived probability. It is only worth its weight if its decision survives the downstream reconciliation to the projected score.

On all 1 games with an applied blend, the blend's side and the published side agree.

Blend side survived on 1 of 1 games; the blend flagged a winner change on 0.

Repeated bias across slates, and the lever that moves it

A bias on one slate is noise. The same sign across slates, large relative to how much it moves between them, is a model defect. Only the ones that pass both tests are turned into a named parameter change; the rest are held deliberately.

starter ERA error (actual minus projected)

Mean -0.17 over 9 slates (sign shared by 0.56 of them, z = -0.40).

starters beat their projection: the run model credits opposing offenses with more than they produced.

Hold: no change: this bias is not separable from slate-to-slate noise yet

5 of 9 slates share the sign, mean -0.17 +/- 0.42 standard error: not separable from noise

lineup runs actual minus projected

Mean -0.61 over 9 slates (sign shared by 0.67 of them, z = -1.69).

lineups scored below projection: the run environment is set too high.

Hold: no change: this bias is not separable from slate-to-slate noise yet

6 of 9 slates share the sign, mean -0.61 +/- 0.36 standard error: not separable from noise

SlateGamesWinner accMean starter ERA errorMean lineup runs vs projSides broke on pitchingSides broke on offense
20261009———
2026100811.0002.311.00
2026100740.7500.85-0.3812
2026100621.000-1.40-1.251
2026100520.000-1.11-0.752
2026100420.500-1.24-2.002
2026100341.000-0.95-2.254
20261002———
2026100111.0000.000.50
2026093040.7500.780.121
2026092941.000-0.76-0.503
20260928———

Score distribution and margin compression

Narrow predicted margins next to wide actual margins is the signature the score-variance tail is too tight.

Predicted margins ≤2: 1 · Actual margins ≥4: 0
GamePred marginActual marginPred − actual
CHW@CLE12-1

Per-game evidence coverage

Expected games
1
Artifacts loaded
1
Structural audits
1
Deep-audit games
1
Learning rows
1
Starter comparisons
1

Every game, in depth (1)

CHW@CLEHIT

Predicted: CLE 5-6 (conf +0.05, lean)Actual: CLE 0-2Brier 0.224total bias +9
Root cause: Right winner, wrong score
Evidence-backed diagnosis
Quantified contributing factors
TeamStarterProjectedActualER err
CHWSean Burke5 ER / 13 outs2 ER / 15 outs-3
CLEGavin Williams1 ER / 14 outs0 ER / 17 outs-1
Decision internals: run factors home×0.99 / away×0.968; savant lineup adjustment applied

Player-level breakdown (projected vs actual)

Every value is actual / projected. Run impact approximates how far each hitter's real line moved run expectancy from its projection; it orders the movers and is not a published stat.

Top deviations that drove the game:

Pitcher versus batter: what actually broke this game

Per-pitch matchup fields are not populated in the current feeds, so this is reconstructed from the settled box: each starter's workload-adjusted ERA, the bullpen share behind him, and the opposing lineup's real production against its projection, with the hitters who beat that projection named.

AWAY pitching

No settled pitching line for this club. The forecast named Sean Burke (CHW) at a projected 10.38 ERA, but the per-player feed carries no pitching row for him in this game, so the actual-versus-projected comparison cannot be made on this side. That is a source-coverage gap in the settled box, not a forecasting failure.

Bullpen behind him: 0 ER over 0 outs.

The HOME lineup he faced produced 2 runs on 6 hits and 1 HR, against a projected 6 runs / 8 hits (-4 runs vs projection).

Who did the damage to him:

  • Petey Halpin: 2-for-3, 0 HR, 0 RBI [+1.56 runs vs projection] season xwOBA 0.295, below average - a good day, not a model error
  • José Ramírez: 1-for-3, 1 HR, 2 RBI [+0.33 runs vs projection] season xwOBA 0.325, above average - a good day, not a model error

Verdict: neither side broke materially - the result is closer to variance

HOME pitching

Gavin Williams (CLE) threw 17 outs, 0 ER = 0 ERA against a projected 1.93 ERA (-1.93 ERA error)

Bullpen behind him: 0 ER over 4 outs.

The AWAY lineup he faced produced 0 runs on 0 hits and 0 HR, against a projected 0 runs / 0 hits (0 runs vs projection).

No individual hitter beat his projection by a meaningful margin.

Verdict: offense: the lineup scored well below its projection

Starting pitchers & relievers: actual / projected + context (ERA is workload-aware: ER over 9 innings, so a short blow-up is not read like a quality start; ERA error in parentheses when material. exp BB and exp SO are the continuous rate expectations. The integer beside each is a simulation draw reconciled to the opposing simulated batting box, so it is not the line that ranks pitchers: on the 2026-09-07 slate the integers published 39 walks and 121 strikeouts against 51 and 130 real, while these expectations landed on 50.4 and 132.6.)

PitcherTeamOutsERAERHHRBBexp BBSOexp SOContext (as-of)
CLEGavin Williams (Starter)17 / 140 / 1.930 / 11 / 20 / 02 / 42.1412 / 107.21venue home: 2.88 vs 5.05 ERA (ok) · opp run factor 0.97 (average) · 34 prior appearances this season
CLEHunter Gaddis (Middle Reliever (High Leverage))4 / 30 / 9 (-9.00)0 / 12 / 10 / 00 / 00.264 / 20.89

Hitters: actual / projected (sorted by run impact vs projection)

BatterTeamABH2B3BHRRBIRBBSORun impactSeason xwOBASignal
Petey Halpin (CF)CLE3 / 42 / 02 / 00 / 00 / 00 / 00 / 00 / 00 / 11.560.295 below averagegood day
Nathaniel Lowe (1B)CLE3 / 40 / 10 / 00 / 00 / 10 / 20 / 10 / 00 / 2-1.40.335 above averagebad day
Patrick Bailey (C)CLE3 / 30 / 10 / 00 / 00 / 00 / 00 / 10 / 10 / 1-0.80.307 averageno signal
Steven Kwan (LF)CLE3 / 41 / 20 / 00 / 00 / 00 / 01 / 11 / 11 / 0-0.470.328 above average—
Brayan Rocchio (SS)CLE3 / 40 / 10 / 00 / 00 / 00 / 00 / 10 / 02 / 0-0.470.294 below average—
José Ramírez (3B)CLE3 / 51 / 10 / 00 / 01 / 12 / 11 / 11 / 01 / 10.330.325 above average—
Chase DeLauter (RF)CLE4 / 31 / 10 / 00 / 00 / 00 / 10 / 00 / 10 / 0-0.330.346 elite—
Travis Bazzana (2B)CLE3 / 30 / 00 / 00 / 00 / 00 / 00 / 00 / 12 / 1-0.330.299 below average—
Jo Adell (DH)CLE4 / 41 / 10 / 10 / 00 / 00 / 10 / 10 / 01 / 2-0.310.329 above average—
Full model trace, player evidence, and audit findings

Fundamental evidence entering the pick

SignalHome-away edgeMeaning
Season quality-0.161positive favors home; negative favors away
Recent form-0.03positive favors home; negative favors away
Starting-pitcher matchup0.022positive favors home; negative favors away
Composite0.134positive favors home; negative favors away

Score and confidence evolution

StageAway-home runsConfidenceWhat changed
historical_ml4.08-4.86n/aBase ML historical model prediction
variance_applied4-5n/aDeterministic baseline target (variance factor 1.0)
enhanced_prediction5-60.527Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer5-6n/aSavant KPI blend computed and withheld; baseline kept
embedded_savant_run_environment5-6n/aTarget score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review5-6n/aRefreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target5-6n/aCapped at max 12 realistic runs
simulation_result5-6n/aFinal inning-by-inning simulation result

Official postgame stage attribution

StageBeforeAfterToward final pickWhat changed
variance_applied4.08-4.864-50.222Deterministic baseline target (variance factor 1.0)
enhanced_prediction4-55-60Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer5-65-60Savant KPI blend computed and withheld; baseline kept
embedded_savant_run_environment5-65-60Target score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review5-65-60Refreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target5-65-60Capped at max 12 realistic runs
simulation_result5-65-60Final inning-by-inning simulation result

Largest player-level adjustments from the ultra-detailed trace

These are pregame model adjustments, not claims about actual postgame player error.

TeamPlayerRoleNet effectLargest change
CLEGavin Williamspitcher / Starterbetterpredicted_H -7
CHWSean Burkepitcher / Starterworsepredicted_BB 3
CLETanner Bibeepitcher / Setup Manworsepredicted_ER 3
CHWBrenton Doylebatter / CFworsepredicted_SO 2.026
CHWSean Newcombpitcher / Long Relieverbetterpredicted_ER -2
CHWNoah Schultzpitcher / Long Relieverbetterpredicted_H -2
CHWJordan Hickspitcher / Middle Relieverworsepredicted_SO -2
CLEDaniel Espinopitcher / Middle Reliever (High Leverage)betterpredicted_SO 2

Structural audit findings

SeverityRuleFindingSubject
infoRECONCILIATION_PROPAGATIONNo score_target_reconciliation step was used for this game.

Cross-game lever tension

Each candidate fix, and exactly which games it would help versus hurt. A lever that repairs one game and breaks two is visible here before it is proposed.

score.variance_multiplier / score.variance_floor (widen run distributions)

Targets: brier_score, calibration_error · 0 helped vs 0 hurt
Would help
  • none
Would hurt / risk
  • none

player.pitcher.v4 form weights / player.pitcher_prior_games

Targets: starter_er_mae, starter_outs_mae · 1 helped vs 0 hurt
Would help
  • CHW@CLE (hit): starter ER off by 3
Would hurt / risk
  • none

recent.* / season.* run-mean weighting

Targets: team_run_mae, total_run_mae, accuracy · 1 helped vs 0 hurt
Would help
  • CHW@CLE (hit): team runs off by 9
Would hurt / risk
  • none

Day over day: did it improve or worsen

Compared against packet 20261009. Last recorded change: v15.28.3 (2026-10-07) Audit the confidence blend against the adaptive cap actually in force.

MetricPriorCurrentΔResult
brier_score0.24530.245-0.000278improved
accuracy0.61060.6195+0.0089improved
team_run_mae2.39822.4292+0.031regressed
total_run_mae3.59293.6549+0.062regressed
calibration_error0.12380.1325+0.0087regressed
starter_er_mae1.64021.6435+0.0033regressed
starter_outs_mae4.23834.2222-0.0161improved

The adjustment the system made in response

Status: skipped open rollback monitor.

Luna deep post-mortem (full)

1. Evidence receipt and gaps

All seven source_manifest entries were marked loaded:

  1. prediction review — /app/output/reports/prediction_review_20261010.json, 11,425 bytes; official outcomes and scoring errors.
  2. forensic deep audit — /app/output/reports/PREDICTION_SYSTEM_DEEP_AUDIT_20261010.json, 30,956 bytes; probability, provenance, starter, and decision contracts.
  3. continuous learning — /app/output/learning/continuous_learning_daily_20261010.json, 185,336 bytes; pipeline-stage quality, calibration, probability lineage, score distribution, and official starter comparisons.
  4. detailed report — /app/output/reports/detailed_20261010.html, 33,426 bytes; full game and simulation rendering.
  5. ultra detailed player audit — /app/output/reports/20261010_ultra_detailed_player_audit.html, 1,811,791 bytes; player-level prediction trace.
  6. structural audit — /app/output/reports/audit_report_20261010.html, 128,231 bytes; invariant findings.
  7. integrity revision audit — /app/output/reports/audit_report_20261010_integrity_revision.html, 365,249 bytes; structural audit of three post-start revision artifacts.

Slate coverage: one game was expected, reviewed, structurally audited, included in continuous learning, and given a starter comparison: each corresponding coverage_matrix count is 1/1. The sole game, CHW@CLE, was a hit on the winner, not a loss. Full coverage does not remove the game-level run-score and model-quality concerns.

Gaps and internal inconsistencies:

2. Executive diagnosis

DimensionDiagnosis
Winner accuracy1/1 (100%), but this is one game. CLE was predicted and won. The cross-slate report gives a historical walk-forward winner accuracy of 0.570149; this slate alone does not establish improvement.
Calibration qualityThe only published pick had probability 0.526845 and hit, producing Brier 0.223876. On this one observation, confidence was below the observed hit rate (1.0), hence the bucket’s reported underconfidence, not overconfidence. The bucket has only one settled game; its absolute calibration error of 0.4732 is therefore not a stable calibration estimate. Cross-slate weighted calibration error is explicitly regressing, so it warrants monitoring and shadow testing, not a conclusion that this particular hit was overconfident.
Score accuracyPoor: predicted CHW 5, CLE 6 versus actual CHW 0, CLE 2. Team-run absolute error sums to 9; total runs were overprojected by 9 (11 predicted vs 2 actual). The winner being right does not make this a good score prediction.
Starter accuracyBoth starters were projected to allow more earned runs than they did; both also recorded more outs than projected. Burke’s projected-to-actual ER gap was 5 to 2; Williams’s was 1 to 0. This supports a starter/run-model miss on this game, but one game cannot establish a starter bias.
Artifact integrityThe structural audit passed, with 0 critical, 0 error, 0 warning, and 1 info finding; the game diagnostics report forecast-file integrity clean (0 defects, 1 informational note). No evidence says an artifact defect caused this game’s result. The probability-field mismatch and missing explanation of recency are separate traceability concerns, not recorded structural-audit failures.

Causal issue register reconciliation:

No causal issue in the register identifies a winner miss: there was none. The material observed failure is the run-score miss, with very weak historical run-model validation signal.

3. Every game

CHW@CLE — hit on winner, wrong score

4. Miss reconstruction

There are no game losses to reconstruct: misses: 0, loss_primary_drivers: {}, and CLE was the correct predicted winner. There is therefore no earliest stage at which evidence moved the pick toward a wrong result.

The score miss can still be traced, without misclassifying it as a winner miss:

Pipeline stage quality across all stages and transitions:

StageTeam-run MAETotal-run MAEMargin MAEWinner
historical_ml3.47116.94221.22241/1
variance_applied3.57.01.01/1
enhanced_prediction4.59.01.01/1
kpi_layer4.59.01.01/1
embedded_savant_run_environment4.59.01.01/1
fundamental_edge_target_review4.59.01.01/1
capped_target4.59.01.01/1
simulation_result4.59.01.01/1
published_final4.59.01.01/1

All eight transitions are reported: historical ML→variance applied, variance applied→enhanced, enhanced→KPI, KPI→embedded Savant, embedded Savant→fundamental review, fundamental review→capped target, capped target→simulation, and simulation→published final. No transition changed winner direction; all have winner-hit delta 0 and no direction-change games. The historical-ML→variance transition raised team-run MAE by 0.0289 while improving margin MAE by 0.2224. Variance→enhanced raised team-run MAE by 1.0 with no margin change. Every later transition had zero measured score-metric change. The eventual correct winner does not erase the intermediate team-run regression.

A home-away confidence edge of 0.12, if encountered, is moderate—not a near coin flip. This game’s edge was 0.0537, in the lean bucket.

5. Cross-game counterfactuals

There is only one game, so no genuine across-game counterfactual can be measured. For every lever_tension entry:

  1. score.variance_multiplier / score.variance_floor (widen run distributions) — helps: none listed; hurts: none listed; net evidence: 0 helped / 0 hurt. No game-specific evidence supports changing it from this entry. It targets Brier/calibration in the tension record, while score variance would not by itself correct a biased run mean.
  2. player.pitcher.v4 form weights / player.pitcher_prior_games — helps: CHW@CLE, noted as a hit with starter ER off by 3; hurts: none listed. This is a one-game directional lead, not adequate evidence for changing pitcher weights.
  3. recent.* / season.* run-mean weighting — helps: CHW@CLE, noted as a hit with team runs off by 9; hurts: none listed. A lower run mean might address the direction of this score error, but the lone game cannot identify which weighting caused it or establish net benefit.

Tempting one-game fixes to avoid: do not tune starter weights solely to Burke’s or Williams’s lower-than-projected ER; do not lower CLE’s run mean solely because the lineup underperformed; do not fit the player model to the listed individual deviations; do not widen score variance as if it necessarily fixes an overhigh mean; and do not lower confidence caps on the claim that this hit was overconfident. These moves are unsupported by the one-game result and can damage other slates or metrics.

6. Data and contract defects

Audit findings by severity:

Coverage reconciliation: expected, reviewed, structurally audited, continuously learned, starter-compared, and deep-audited counts are all 1/1; one canonical artifact set was loaded. Coverage is complete, but it does not make the run prediction accurate or erase within-game findings.

Prediction-model defects versus presentation/artifact issues:

Pick-side probability lineage, as supplied:

  1. Raw model: lineage says 0.5627; model trace instead calls 0.53629 the raw pick probability. The conflict is unresolved.
  2. Calibrated: 0.5372, calibration sample size 739, empirical hit rate 0.5683.
  3. Governor: input 0.53629, output 0.5372.
  4. Score coherence: 0.537156.
  5. Published: 0.526845; published-minus-calibrated −0.010355. The record attributes this to score coherence followed by a matchup-recency guardrail and says unexplained_material_delta: false.

The sequence includes recorded transformations and therefore does not establish an unrecorded material bypass. But the raw-probability mismatch, null recency factor/reason, and stated delta do prevent a fully reproducible arithmetic trace from the supplied evidence. The publication change is documented by name but not numerically attributable to each step. Record these as a traceability gap, not as a proven forecast-file defect.

7. Cross-slate persistence

Structural evidence:

Every finding_streaks entry:

FindingConsecutive slatesPresent now?Interpretation
pipeline_winner_instability0No2 incidences in the 11-slate window; no current consecutive streak.
score_margin_compression0No3 incidences in window; target levers are score.variance_multiplier and score.variance_floor, but not present now.
simulation_inert_on_slate11YesPresent on all 11 consecutive slates; escalated established failure.
single_slate_calibration_instability1Yes9 incidences in window; current, but only one consecutive slate.
weak_run_model_signal1Yes9 incidences in window; current, but only one consecutive slate.

Escalated finding: simulation_inert_on_slate has 11 consecutive slates and is explicitly escalated. Target lever listed: simulation.allow_score; target metrics: team-run MAE and total-run MAE. The finding says it is not parameter-actionable and directs a code/diagnostic action: confirm the simulation is running rather than silently no-oping. Its root-cause evidence in the self-assessment is that the same target-search draws are used to construct a win-probability distribution, with early exit after finding a target-realizing sequence; a default draw count around 2 makes the resulting win rate uninformative. The diagnosis proposes separating target-realization search from an independent, unsteered probability batch. Treat this as an established process failure, not single-slate noise.

Every metric_trends direction:

These trend labels are not a claim that each metric is well measured on every slate; the series includes nulls and small samples.

Top-confidence-pick record: loss streak 0. Listed results include hits on 2026-09-30, 2026-10-01, 2026-10-03, 2026-10-04, 2026-10-06, 2026-10-08, and 2026-10-10; misses on 2026-10-05 and 2026-10-07; and two unknown-result entries with blank dates. Thus the current top pick was a hit, with no active loss streak.

8. Adjustments for today

Ranked by persistence and scope:

  1. Escalated 11-slate simulation inertness — code/diagnostic action, not a forced parameter move.
  1. Single-slate strongest driver: high run-score overprojection / weak run signal — operator feature-and-validation action, not nightly weight tuning.
  1. Calibration: monitor and run a bounded shadow comparison; do not blindly lower caps.

No change to pitcher weights or season/recent run means is recommended today: their one-game tension evidence has no cross-game harms listed, but neither does it establish net benefit. This abstention reflects insufficient directionally reliable evidence for those moves, not a claim that the high run score was acceptable.

9. Bottom line

Known: CLE was correctly selected at published probability 0.526845, but the score prediction was badly high—11 predicted runs versus 2 actual, with team-run error 9. The structural audit passed, and no artifact defect is identified as the cause. The supplied probability trace nevertheless has a raw-probability field mismatch and incomplete recency metadata. Run-model holdout R² is near zero; the simulation-inertness finding has persisted for 11 consecutive slates and is escalated.

Uncertain: whether this game’s run miss reflects a repeatable mean bias, a starter-model issue, lineup variance, or some combination; whether the apparent calibration trend can be corrected by any particular confidence weight; and how much an independently sampled simulation would change published probabilities.

Safest next action for the very next slate: instrument and verify the simulation path in a non-promoted shadow/diagnostic run, separating its score-realization search from an independent win-probability sample. This directly addresses the strongest persistent, actionable process failure without making a one-game parameter adjustment.